# len(evaluation_set_read),
# len(evaluation_set_unread)))
#learn on subset
#user_model = UserModelBayes(user_id = user.id,
# extractor = feature_extractor)
#user_model = UserModelCentroid(user_id = user.id,
# extractor = feature_extractor)
user_model = UserModelSVM(user_id = user.id,
extractor = feature_extractor)
#user_model = UserModelTree(user_id = user.id,
# extractor = feature_extractor)
user_model.set_samples_sizes(p_synthetic, p_majority)
#user_model.set_samples_sizes(p_synthetic_samples = None,
# p_majority_samples = None)
#user_model = UserModelMeta(user_id = user.id,
# extractor = feature_extractor)
user_model.train(read_article_ids = training_set_read,
unread_article_ids = training_set_unread)
#Set y_true
y_true = np.empty(shape=(len(evaluation_set_read) + len(evaluation_set_unread)))
y_true[:len(evaluation_set_read)] = user_model.READ
y_true[len(evaluation_set_read):] = user_model.UNREAD
#Set y_pred
